BFT-IoMT: A Blockchain-Based Trust Mechanism to Mitigate Sybil Attack Using Fuzzy Logic in the Internet of Medical Things.

Numerous sensitive applications, such as healthcare and medical services, need reliable transmission as a prerequisite for the success of the new age of communications technology. Unfortunately, these systems are highly vulnerable to attacks like Sybil, where many false nodes are created and spread with deceitful intentions. Therefore, these false nodes must be instantly identified and isolated from the network due to security concerns and the sensitivity of data utilized in healthcare applications. Especially for life-threatening diseases like COVID-19, it is crucial to have devices connected to the Internet of Medical Things (IoMT) that can be believed to respond with high reliability and accuracy. Thus, trust-based security offers a safe environment for IoMT applications. This study proposes a blockchain-based fuzzy trust management framework (BFT-IoMT) to detect and isolate Sybil nodes in IoMT networks. The results demonstrate that the proposed BFT-IoMT framework is 25.43% and 12.64%, 12.54% and 6.65%, 37.85% and 19.08%, 17.40% and 8.72%, and 13.04% and 5.05% more efficient and effective in terms of energy consumption, attack detection, trust computation reliability, packet delivery ratio, and throughput, respectively, as compared to the other state-of-the-art frameworks available in the literature.

Peripapillary atrophy classification using CNN deep learning for glaucoma screening.

Glaucoma is the second leading cause of blindness worldwide, and peripapillary atrophy (PPA) is a morphological symptom associated with it. Therefore, it is necessary to clinically detect PPA for glaucoma diagnosis. This study was aimed at developing a detection method for PPA using fundus images with deep learning algorithms to be used by ophthalmologists or optometrists for screening purposes. The model was developed based on localization for the region of interest (ROI) using a mask region-based convolutional neural networks R-CNN and a classification network for the presence of PPA using CNN deep learning algorithms. A total of 2,472 images, obtained from five public sources and one Saudi-based resource (King Abdullah International Medical Research Center in Riyadh, Saudi Arabia), were used to train and test the model. First the images from public sources were analyzed, followed by those from local sources, and finally, images from both sources were analyzed together. In testing the classification model, the area under the curve's (AUC) scores of 0.83, 0.89, and 0.87 were obtained for the local, public, and combined sets, respectively. The developed model will assist in diagnosing glaucoma in screening programs; however, more research is needed on segmenting the PPA boundaries for more detailed PPA detection, which can be combined with optic disc and cup boundaries to calculate the cup-to-disc ratio.

Cross-Sensor Fingerprint Enhancement Using Adversarial Learning and Edge Loss.

A fingerprint sensor interoperability problem, or a cross-sensor matching problem, occurs when one type of sensor is used for enrolment and a different type for matching. Fingerprints captured for the same person using various sensor technologies have various types of noises and artifacts. This problem motivated us to develop an algorithm that can enhance fingerprints captured using different types of sensors and touch technologies. Inspired by the success of deep learning in various computer vision tasks, we formulate this problem as an image-to-image transformation designed using a deep encoder-decoder model. It is trained using two learning frameworks, i.e., conventional learning and adversarial learning based on a conditional Generative Adversarial Network (cGAN) framework. Since different types of edges form the ridge patterns in fingerprints, we employed edge loss to train the model for effective fingerprint enhancement. The designed method was evaluated on fingerprints from two benchmark cross-sensor fingerprint datasets, i.e., MOLF and FingerPass. To assess the quality of enhanced fingerprints, we employed two standard metrics commonly used: NBIS Fingerprint Image Quality (NFIQ) and Structural Similarity Index Metric (SSIM). In addition, we proposed a metric named Fingerprint Quality Enhancement Index (FQEI) for comprehensive evaluation of fingerprint enhancement algorithms. Effective fingerprint quality enhancement results were achieved regardless of the sensor type used, where this issue was not investigated in the related literature before. The results indicate that the proposed method outperforms the state-of-the-art methods.

Predicting isoscapes based on an environmental similarity model for the geographical origin of Chinese rice.

The authentication of geographical origin of food is important using stable isotope analysis. However, the isotopic databank is still short of comprehensive. The isoscapes model based on environmental similarity is used for the first time to predict the geospatial distribution of δ13C, δ2H and δ18O in Chinese rice in 2017 and 2018. 794 rice samples in 2017 were used to build isoscapes model. Independent verification shows that the predicted isotope distribution from this new approach is of high accuracy, with a root mean square error (RMSE) of 0.51 ‰, 7.09 ‰ and 2.06 ‰ for δ13C, δ2H and δ18O values for 2017, respectively. Our results indicate that it is possible to predict the spatial distribution of stable isotopes in rice using an isoscapes model based on environmental similarity. This novel strategy can enrich and complement a stable isotope reference database for rice origin identification at regional scale.

A Prolonged History of Denture Impaction for 12 Weeks In Situ.

Foreign body ingestion has serious consequences if left untreated. Impacted dentures for a prolonged period can lead to life-threatening complications. Therefore, prompt diagnosis and immediate intervention are lifesaving. Our patient presented to his local accident and emergency department after having swallowed his dentures during a meal. Initial investigations and workup detected no abnormalities and he was discharged back to the community. Twelve weeks following ingestion, he had developed dysphagia and weight loss which prompted an urgent referral for oesophago-gastro-duodenoscopy (OGD). This identified the dentures impacted within the upper oesophagus and initial attempts at removal were unsuccessful, therefore he required hospital admission for alternative feeding in the interim. A joint procedure with the Ear, Nose and Throat and upper gastrointestinal surgeons was carried out to successfully remove the dentures endoscopically. The patient made an immediate recovery, resuming his normal oral diet with appropriate follow up after discharge. It is suspected our patient had an impacted denture for a period of 12 weeks without sustaining any life-threatening complications, which makes this case rather unique. This case highlights the importance of thorough and careful clinical history taking and examination.

Context-Aware Pending Interest Table Management Scheme for NDN-Based VANETs.

In terms of delivery effectiveness, Vehicular Adhoc NETworks (VANETs) applications have multiple, possibly conflicting, and disparate needs (e.g., latency, reliability, and delivery priorities). Named Data Networking (NDN) has attracted the attention of the research community for effective content retrieval and dissemination in mobile environments such as VANETs. A vehicle in a VANET application is heavily reliant on information about the content, network, and application, which can be obtained from a variety of sources. The information gathered can be used as context to make better decisions. While it is difficult to obtain the necessary context information at the IP network layer, the emergence of NDN is changing the tide. The Pending Information Table (PIT) is an important player in NDN data retrieval. PIT size is the bottleneck due to the limited opportunities provided by current memory technologies. PIT overflow results in service disruptions as new Interest messages cannot be added to PIT. Adaptive, context-aware PIT entry management solutions must be introduced to NDN-based VANETs for effective content dissemination. In this context, our main contribution is a decentralised, context-aware PIT entry management (CPITEM) protocol. The simulation results show that the proposed CPITEM protocol achieves lower Interest Satisfaction Delay and effective PIT utilization based on context when compared to existing PIT entry replacement protocols.

Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition.

Sign language is the main channel for hearing-impaired people to communicate with others. It is a visual language that conveys highly structured components of manual and non-manual parameters such that it needs a lot of effort to master by hearing people. Sign language recognition aims to facilitate this mastering difficulty and bridge the communication gap between hearing-impaired people and others. This study presents an efficient architecture for sign language recognition based on a convolutional graph neural network (GCN). The presented architecture consists of a few separable 3DGCN layers, which are enhanced by a spatial attention mechanism. The limited number of layers in the proposed architecture enables it to avoid the common over-smoothing problem in deep graph neural networks. Furthermore, the attention mechanism enhances the spatial context representation of the gestures. The proposed architecture is evaluated on different datasets and shows outstanding results.

Migratory Foreign Bodies in the Aerodigestive Tract: The Importance of CT Imaging.

Accidental ingestion of foreign bodies forms a major part of otorhinolaryngological emergencies. It is dangerous, as the foreign bodies tend to perforate the aerodigestive tract. Since endoscopy is diagnostic as well as therapeutic, it is preferred over computed tomography (CT) scan, especially in developing countries. We present a case of a middle-aged man who presented with fever, neck swelling, and a five-day history of accidental ingestion of a foreign body. He underwent upper gastrointestinal endoscopy, which came out as normal. CT) imaging was performed, which showed migration of the foreign body to the parapharyngeal space and resulting abscess formation. The abscess was drained, and the foreign body was removed transcervically. We discuss this case to stress the role of CT imaging in the diagnosis of foreign bodies of the upper aerodigestive tract and propose an algorithm for the management of such cases. Upper gastrointestinal endoscopy alone would be insufficient to diagnose perforating and migrating foreign bodies, which may cause severe complications if left undiagnosed.

VKORC1 gene polymorphism (-1639G>A) in warfarin therapy patients of Pakistani population.

OBJECTIVE: To observe vitamin K epoxide reductase complex subunit 1-1639 G>A polymorphism in patients resistant to warfarin therapy, and to calculate the allele frequency of the polymorphism in local patients. Methods: The cross-sectional case-control study was conducted at the Punjab Institute of Cardiology, Lahore, from 2013 to 2014 and comprised patients with heart valve replacement. Thy were divided into warfarin-resistant group 1 taking 10mg/day, 70mg/week and control group 2 taking a standard dose of 5mg/day, 35mg/week. The vitamin K epoxide reductase complex subunit 1-1639 G>A polymorphism analysis was done by polymerase chain reaction, followed by restriction fragment length polymorphism technique. Data was analysed using SPSS 20. RESULTS: Of the 146 patients, there were 73(50%) in each of the two groups. In group 1, there were 37(50.68%) males and 36(49.32%) were females with an overall mean age of 33±12 years, while group 2 had 36(49.32%) males and 37(50.68%) females with an overall mean age of 37±13 years. There were no significant differences in mean values of age, serum cholesterol, triglycerides and albumin levels between the groups (p>0.05). The G allele was the most frequently found in both groups, with 140(96%) in group-1 and 137(94%) in group-2. Overall, the homozygous GG genotype was significantly higher in the sample 132(90.4%) (p<0.05). CONCLUSIONS: There was evidence found that vitamin K epoxide reductase complex subunit 1-1639 G>A polymorphism alone may not be the dominant genetic factor associated with warfarin response variability.

Prognostic Value of Intracellular Transcription of Factors HIF-1α and p53 and Their Relation to Estradiol and TNM Parameters of Breast Cancer Tissues in Women with Invasive Ductal Carcinoma in Thi-Qar Province, Iraq.

Breast cancer is the most common malignancy affecting women's health, with an increasing incidence worldwide. This study aimed to measure the intracellular concentration of the hypoxia-inducible factor 1 α (HIF-1α), tumor suppression protein p53, and estradiol (E2) in tumor tissues of adult females with breast cancer and their relation to tumor grade, tumor size, and lymph node metastases (LNM). The study was conducted on 65 adult female participants with breast mass admitted to the operating theater in Al-Hussein Teaching Hospital and Al-Habboby Teaching Hospital in Nasiriyah, Iraq, from January to November 2021. Fresh breast tumor tissues were collated and homogenized for intracellular biochemical analysis using the enzyme-linked immunosorbent assay method. In total, 44 (58%) out of 65 patients, in the age range of 18-42 years and the mean±SD age of 32.55±6.40 years, had fibroadenomas, and other 21 (42%) cases, in the age range of 32-80 years and the mean±SD age of 56±14.4 years had invasive ductal carcinoma (IDC) breast cancer. Intracellular levels of HIF-1α, p53, and E2 were elevated significantly (P<0.001) in IDC cases compared to the benign group. The most malignant tumors of IDC cases were in grade III and sizes T2 and T3. The tissue concentrations of HIF-1α, P53, and E2 were significantly elevated in patients with tumor stage T3 compared to T2 and T1. A significant elevation was found in the levels of HIF-1α, p53, and E2 in the positive LNM subgroup compared to the negative LNM group. Based on the obtained results, the prognostic value of the intracellular HIF-1α is considered to be a useful prognostic factor in Iraqi women with ICD and the combination of a HIF-1α protein with the nonfunctional p53 and E2 tends to indicate the proliferation, invasiveness, and metastases of the breast tumors.

Sensor-Based Human Activity Recognition with Spatio-Temporal Deep Learning.

Human activity recognition (HAR) remains a challenging yet crucial problem to address in computer vision. HAR is primarily intended to be used with other technologies, such as the Internet of Things, to assist in healthcare and eldercare. With the development of deep learning, automatic high-level feature extraction has become a possibility and has been used to optimize HAR performance. Furthermore, deep-learning techniques have been applied in various fields for sensor-based HAR. This study introduces a new methodology using convolution neural networks (CNN) with varying kernel dimensions along with bi-directional long short-term memory (BiLSTM) to capture features at various resolutions. The novelty of this research lies in the effective selection of the optimal video representation and in the effective extraction of spatial and temporal features from sensor data using traditional CNN and BiLSTM. Wireless sensor data mining (WISDM) and UCI datasets are used for this proposed methodology in which data are collected through diverse methods, including accelerometers, sensors, and gyroscopes. The results indicate that the proposed scheme is efficient in improving HAR. It was thus found that unlike other available methods, the proposed method improved accuracy, attaining a higher score in the WISDM dataset compared to the UCI dataset (98.53% vs. 97.05%).

Transcutaneous fluorescence spectroscopy as a tool for non-invasive monitoring of gut function: first clinical experiences.

Gastro-intestinal function plays a vital role in conditions ranging from inflammatory bowel disease and HIV through to sepsis and malnutrition. However, the techniques that are currently used to assess gut function are either highly invasive or unreliable. Here we present an alternative, non-invasive sensing modality for assessment of gut function based on fluorescence spectroscopy. In this approach, patients receive an oral dose of a fluorescent contrast agent and a fibre-optic probe is used to make fluorescence measurements through the skin. This provides a readout of the degree to which fluorescent dyes have permeated from the gut into the blood stream. We present preliminary results from our first measurements in human volunteers demonstrating the potential of the technique for non-invasive monitoring of multiple aspects of gastro-intestinal health.

Knowledge, attitude, practice and perception regarding COVID-19 among students in Bangladesh: Survey in Rajshahi University

BackgroundThe number of infection and death by COVID-19 has been rapidly increasing since December 2019 in all over the world. Until now, there is no specific treatment or vaccine for this disease; WHO suggests only some protective measures like maintaining social distance, staying home, washing hands with soap or sanitizer, wearing mask etc. The objective of this study was to survey knowledge, attitude, practice and perception regarding COVID-19 among students in Rajshahi University, Bangladesh. MethodsWe collected data from 305 students of Rajshahi University for this cross-sectional study using mixed sampling from March 11 to March 19, 2020. Frequency distribution, Mann-Whitney and Kruskal-Wallis tests were used in this study. ResultsOut of 305 participants, 224 (73.4%) and 81 (26.6%) were male and female students respectively. The study revealed that Rajshahi university students had average knowledge on symptoms, protective way and transmission of COVID-19. Female students were more knowledgeable than male. More than one third of the students had negative attitude to avoiding public transport and going out to public places with friends and family. The practice of students practice during our data collection period and in future was not satisfactory. More than one third of students were not keen to stay at home and avoid going to crowded places. The perception towards COVID-19 was not good; they had no idea whether the outbreak would affect their daily routine, study and financial matters, study field work and restrict leisure time of meeting family and relatives. ConclusionsWe found that general knowledge, attitude, practice and perception of the university students regarding COVID-19 were not satisfactory. This indicated that the situation was worse among common people. In Bangladesh, the number of healthcare providers is insufficient. University students can be employed as potential workforce to create awareness among mass people on prevention of COVID-19.

Progress and prospects in the management of bacterial infections and developments in Phytotherapeutic modalities.

The advent of antibiotics revolutionized medical care resulting in significantly reduced mortality and morbidity caused by infectious diseases. However, excessive use of antibiotics has led to the development of antibiotic resistance and indeed, the incidence of multidrug-resistant pathogens is considered as a major disadvantage in medication strategy, which has led the scholar's attention towards innovative antibiotic sources in recent years. Medicinal plants contain a variety of secondary metabolites with a wide range of therapeutic potential against the resistant microbes. Therefore, the aim of this review is to explore the antibacterial potential of traditional herbal medicine against bacterial infections. More than 200 published research articles reporting the therapeutic potential of medicinal plants against drug-resistant microbial infections were searched using different databases such as Google Scholar, Science Direct, PubMed and the Directory of Open Access Journals (DOAJ), etc., with various keywords like medicinal plants having antibacterial activities, antimicrobial potentials, phytotherapy of bacterial infection, etc. Articles were selected related to the efficacious herbs easily available to local populations addressing common pathogens. Various plants such as Artocarpus communis, Rheum emodi, Gentiana lutea L., Cassia fistula L., Rosemarinus officinalis, Argemone maxicana L, Hydrastis canadensis, Citrus aurantifolia, Cymbopogon citrates, Carica papaya, Euphorbia hirta, etc, were found to have significant antibacterial activities. Although herbal preparations have promising potential in the treatment of multidrug-resistant bacterial infection, still more research is required to isolate phytoconstituents, their mechanism of action as well as to find their impacts on the human body.

Susceptibility pattern of tracheal tube isolates from Intensive Care Unit of Fauji Foundation Hospital Rawalpindi.

OBJECTIVE: To determine the prevalence of resistant pathogens and their antimicrobial susceptibility pattern in an intensive care unit. METHODS: The cross-sectional observational study was conducted at Foundation Hospital, Rawalpindi, Pakistan, from May to September 2016, and comprised tracheal tubes which were collected in sputum culture bottles from patients with clinical findings of ventilator associated pneumonia. The tubes were cultured to locate the resistant pathogens. RESULTS: A total of 113 different strains of bacteria were isolated from 80 patients. The main isolated bacteria was acinetobacter baumannii 45(39.8%) followed by klebsiella pneumonia 14(12.3%) and methicillin-resistant staphylococcus aureus 13(11.5%). Polymyxin B was the most appropriate drug for treating patients infected with acinetobacter baumannii with a sensitivity of 64% while vancomycin and linez oli dhad 100% sensitivity for methicill in - resistant staphylococcusaureus. CONCLUSIONS: Acinetobacter baumannii was the most prevalent strain in tracheal tubes and polymyxin B was the most effective medicine.

Anonymity-preserving Reputation Management System for health sector.

In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time. In this paper, we present a framework for solving the problem of reconciling trust with anonymity in the health sector. Our solution comprises Anonymous Reputation Management (ARM) protocol and Context-aware Trustworthiness Assessment (CTA) protocol. ARM protocol ensures that only those service consumers who received a service from a specific service provider provide a recommendation score anonymously with in the specified time limit. The CTA protocol computes the reputation of a user as a service provider and as a recommender. To determine the correctness of the proposed ARM protocol, formal modelling and verification are performed using High Level Petri Nets (HLPN) and Z3 Solver. Our simulation results verify the accuracy of the proposed context-aware trust assessment scheme.

Rhino Physiognomy: a Myth or Science?

Face reading has been practised since time immemorial by different cultures. Different personality traits have been attributed to different characters of face. It is argued that everyone uses face reading in their daily life when they choose one person to another.One would not prefer to sit beside a tidy, handsome, well-dressed man if he had narrow mean eyes. People tend to artificially change the features of their face to gain acceptance in interviews. Most of these preferences are arbitrary and are born out of the authors' preconceived cultural and social influences. But is there a science behind these observations. The proponents of face reading argue that this is based on clearly stated rules and observation. Nose is an important part of the face. According to face reading the shape and size of nose determines the aggressiveness of the person. The present study tries to scientifically test this statement.

Procalcitonin levels and other biochemical parameters in patients with or without diabetic foot complications.

BACKGROUND: Diagnosis of infection in diabetic foot ulcer (DFU) is not always simple. The analytic precision of procalcitonin (PCT) was evaluated to clarify the use of PCT for distinguish the presence of infection in DFU in comparison to other inflammatory markers. MATERIALS AND METHODS: This study comprised 88 subjects distributed into four groups: 16 nondiabetic healthy subjects (group control), 17 patients with type 2 diabetes mellitus without foot Complication (group DM), 25 patients with noninfected diabetic foot (group NIDF), and 30 patients with infected diabetic foot (group IDF). Fasting blood samples were taken for measurement of glucose, hemoglobin A1C, lipid profile, renal function, erythrocyte sedimentation rate (ESR), and white blood cell (WBC) and its derivatives. Plasma PCT was determined using an enzyme-linked immunosorbent assay. RESULTS: PCT, WBC, ESR, and neutrophils (NEU) were found significantly higher in IDF group than other groups. The receiver operating characteristic analysis showed that sensitivity, specificity, the best cutoff value, and the area under the curve were for ESR (100%, 93%, 31.5 mm/h, 1; P < 0.001), for PCT (87.5%, 86.7%, 66.55 pg/dl, 0.977; P < 0.001), for NEU (93.8%, 93.3%, 5.35, 0.957; P < 0.001) and for WBC (93.8%, 90%, 9.29 × 109/L, 0.942; P < 0.001), respectively. CONCLUSION: The outcomes of this study recommend that PCT can be an asymptomatic marker in the diagnosis of infection in DFU with higher Wagner grades in combination with different inflammatory markers.